# An XAI View on Explainable ASP: Methods, Systems, and Perspectives

arXiv: https://arxiv.org/abs/2601.14764 · HTML: https://mlsanity.com/paper/2601.14764/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 62 references that are in the map.
- First posted on arXiv 21 Jan 2026.

## Builds on (most cited first, 16 of 16)

- [Explanation in Artificial Intelligence: Insights from the Social Sciences](https://mlsanity.com/paper/1706.07269/) (2017)
- [A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts](https://mlsanity.com/paper/2105.07190/) (2021)
- [ASP-Core-2 Input Language Format](https://mlsanity.com/paper/1911.04326/) (2019)
- [Constraint Answer Set Programming without Grounding](https://mlsanity.com/paper/1804.11162/) (2018)
- [Justifying Answer Sets using Argumentation](https://mlsanity.com/paper/1411.5635/) (2014)
- [Reliable Natural Language Understanding with Large Language Models and Answer Set Programming](https://mlsanity.com/paper/2302.03780/) (2023)
- [Answering the "why" in Answer Set Programming - A Survey of Explanation Approaches](https://mlsanity.com/paper/1809.08034/) (2018)
- [Rushing and Strolling among Answer Sets -- Navigation Made Easy](https://mlsanity.com/paper/2112.07596/) (2021)
- [Debugging Non-Ground ASP Programs: Technique and Graphical Tools](https://mlsanity.com/paper/1808.00417/) (2018)
- [Omission-based Abstraction for Answer Set Programs](https://mlsanity.com/paper/2004.01410/) (2020)
- [Explanation Generation for Multi-Modal Multi-Agent Path Finding with Optimal Resource Utilization using Answer Set Programming](https://mlsanity.com/paper/2008.03573/) (2020)
- [Stepwise Debugging of Answer-Set Programs](https://mlsanity.com/paper/1705.06564/) (2017)
- [exp(ASPc) : Explaining ASP Programs with Choice Atoms and Constraint Rules](https://mlsanity.com/paper/2109.08292/) (2021)
- [Model Explanation via Support Graphs](https://mlsanity.com/paper/2310.01626/) (2023)
- [Enablers and Inhibitors in Causal Justifications of Logic Programs](https://mlsanity.com/paper/1602.06897/) (2016)
- [Inconsistency Proofs for ASP: The ASP-DRUPE Format](https://mlsanity.com/paper/1907.10389/) (2019)

## Abstract (arXiv)

Answer Set Programming (ASP) is a popular declarative reasoning and problem solving approach in symbolic AI. Its rule-based formalism makes it inherently attractive for explainable and interpretive reasoning, which is gaining importance with the surge of Explainable AI (XAI). A number of explanation approaches and tools for ASP have been developed, which often tackle specific explanatory settings and may not cover all scenarios that ASP users encounter. In this survey, we provide, guided by an XAI perspective, an overview of types of ASP explanations in connection with user questions for explanation, and describe their coverage by current theory and tools. Furthermore, we pinpoint gaps in existing ASP explanations approaches and identify research directions for future work.